A reasoning diagram based method for fault diagnosis of railway point system

Railway Point System (RPS) is an important infrastructure in railway industry and its faults may have significant impacts on the safety and efficiency of train operations. For the fault diagnosis of RPS, most existing methods assume that sufficient samples of each failure mode are available, which may be unrealistic, especially for those modes of low occurrence frequency but with high risk. To address this issue, this work proposes a novel fault diagnosis method that only requires the power signals generated under normal RPS operations in the training stage. Specifically, the failure modes of RPS are distinguished through constructing a reasoning diagram, whose nodes are either binary logic problems or those that can be decomposed into the problems of the binary logic. Then, an unsupervised method for the signal segmentation and a fault detection method are combined to make decisions for each binary logic problem. Based on the results of decisions, the diagnostic rules are established to identify the failure modes. Finally, the data collected from multiple real-world RPSs are used for validation and the results demonstrate that the proposed method outperforms the benchmark in identifying the faults of RPSs.